




'''simple docstring'''


import time
import unittest

from transformers import is_torch_available
from transformers.testing_utils import require_torch, torch_device

from ..test_modeling_common import ids_tensor


if is_torch_available():
  import torch

  from transformers.generation import (
      MaxLengthCriteria,
      MaxNewTokensCriteria,
      MaxTimeCriteria,
      StoppingCriteriaList,
      validate_stopping_criteria,
  )





@require_torch
class  __lowercase    (	unittest.TestCase			):







   def 		UpperCamelCase__      (						self   ,				UpperCamelCase   )					->     str:
     __a								=       3
     __a								=       250

     __a								=       ids_tensor((batch_size, length)   ,				UpperCamelCase   )
     __a								=       torch.ones((batch_size, length)   ,				device=UpperCamelCase   ,				dtype=torch.float   ) / length
     return input_ids, scores







   def 		UpperCamelCase__      (						self   )					->     Dict:
     __a						,							__a								=       self._get_tensors(5   )

     __a								=       StoppingCriteriaList(
         [
             MaxLengthCriteria(max_length=10   ),
             MaxTimeCriteria(max_time=0.1   ),
         ]   )

     self.assertFalse(criteria(UpperCamelCase   ,				UpperCamelCase   )   )

     __a						,							__a								=       self._get_tensors(9   )
     self.assertFalse(criteria(UpperCamelCase   ,				UpperCamelCase   )   )

     __a						,							__a								=       self._get_tensors(10   )
     self.assertTrue(criteria(UpperCamelCase   ,				UpperCamelCase   )   )







   def 		UpperCamelCase__      (						self   )					->     str:
     __a								=       MaxLengthCriteria(max_length=10   )

     __a						,							__a								=       self._get_tensors(5   )
     self.assertFalse(criteria(UpperCamelCase   ,				UpperCamelCase   )   )

     __a						,							__a								=       self._get_tensors(9   )
     self.assertFalse(criteria(UpperCamelCase   ,				UpperCamelCase   )   )

     __a						,							__a								=       self._get_tensors(10   )
     self.assertTrue(criteria(UpperCamelCase   ,				UpperCamelCase   )   )







   def 		UpperCamelCase__      (						self   )					->     Tuple:
     __a								=       MaxNewTokensCriteria(start_length=5   ,				max_new_tokens=5   )

     __a						,							__a								=       self._get_tensors(5   )
     self.assertFalse(criteria(UpperCamelCase   ,				UpperCamelCase   )   )

     __a						,							__a								=       self._get_tensors(9   )
     self.assertFalse(criteria(UpperCamelCase   ,				UpperCamelCase   )   )

     __a						,							__a								=       self._get_tensors(10   )
     self.assertTrue(criteria(UpperCamelCase   ,				UpperCamelCase   )   )

     __a								=       StoppingCriteriaList([criteria]   )
     self.assertEqual(criteria_list.max_length   ,				10   )







   def 		UpperCamelCase__      (						self   )					->     Union[str, Any]:
     __a						,							__a								=       self._get_tensors(5   )

     __a								=       MaxTimeCriteria(max_time=0.1   )
     self.assertFalse(criteria(UpperCamelCase   ,				UpperCamelCase   )   )

     __a								=       MaxTimeCriteria(max_time=0.1   ,				initial_timestamp=time.time() - 0.2   )
     self.assertTrue(criteria(UpperCamelCase   ,				UpperCamelCase   )   )







   def 		UpperCamelCase__      (						self   )					->     Dict:
     validate_stopping_criteria(StoppingCriteriaList([MaxLengthCriteria(10   )]   )   ,				10   )

     with self.assertWarns(UpperCamelCase   ):
       validate_stopping_criteria(StoppingCriteriaList([MaxLengthCriteria(10   )]   )   ,				11   )

     __a								=       validate_stopping_criteria(StoppingCriteriaList()   ,				11   )

     self.assertEqual(len(UpperCamelCase   )   ,				1   )









'''simple docstring'''


class  __lowercase    :  # Public class to implement a graph







   def __init__(						self   ,				UpperCamelCase   ,				UpperCamelCase   ,				UpperCamelCase   )					->     None:
     __a								=       row
     __a								=       col
     __a								=       graph







   def 		UpperCamelCase__      (						self   ,				UpperCamelCase   ,				UpperCamelCase   ,				UpperCamelCase   )					->     bool:
     return (
         0 <= i < self.ROW
         and 0 <= j < self.COL
         and not visited[i][j]
         and self.graph[i][j]
     )







   def 		UpperCamelCase__      (						self   ,				UpperCamelCase   ,				UpperCamelCase   ,				UpperCamelCase   )					->     None:
     # Checking all 8 elements surrounding nth element
     __a								=       [-1, -1, -1, 0, 0, 1, 1, 1]  # Coordinate order
     __a								=       [-1, 0, 1, -1, 1, -1, 0, 1]
     __a								=       True  # Make those cells visited
     for k in range(8   ):
       if self.is_safe(i + row_nbr[k]   ,				j + col_nbr[k]   ,				UpperCamelCase   ):
         self.diffs(i + row_nbr[k]   ,				j + col_nbr[k]   ,				UpperCamelCase   )







   def 		UpperCamelCase__      (						self   )					->     int:  # And finally, count all islands.
     __a								=       [[False for j in range(self.COL   )] for i in range(self.ROW   )]
     __a								=       0
     for i in range(self.ROW   ):
       for j in range(self.COL   ):
         if visited[i][j] is False and self.graph[i][j] == 1:
           self.diffs(UpperCamelCase   ,				UpperCamelCase   ,				UpperCamelCase   )
           count += 1
     return count



